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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 777 · 40 questions
TalentJR

AI tip (Name the idea, then answer): Learning from examples → AI; fixed rules → a normal program. Order: training data → model → prediction; good data is many, varied and correctly labelled. Generative AI makes new things and can hallucinate; one-sided data causes bias.

NameDateTime takenScore ___ / 40
  1. 1.🔍 Which is the odd one out? (a) wrong labels (b) new data for testing (c) only one kind of example (d) copies of one photo
  2. 2.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
  3. 3.Which of these is good for training a model? (a) very few examples (b) testing on training data (c) wrong labels (d) examples of every type
  4. 4.🧐 Fact or myth: “AI can mix up numbers”? (a) a fact (b) a myth
  5. 5.⏩ In machine learning, which comes first: old emails marked spam or the learned patterns? (a) old emails marked spam (b) the learned patterns
  6. 6.🔍 Which is the odd one out? (a) AI learns from data (b) AI is never wrong (c) AI knows everything (d) confident means correct
  7. 7.📚 Good or bad for training a model: wrong labels? (a) bad for training (b) good for training
  8. 8.Which of these is a fact about AI? (a) AI knows everything (b) AI always checks facts (c) AI answers need checking (d) AI has real feelings
  9. 9.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) True (b) False
  10. 10.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
  11. 11.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) training data (b) the model (c) a prediction
  12. 12.🧐 Fact or myth: “AI is never wrong”? (a) a myth (b) a fact
  13. 13.🛠️ Which does this job need: switching on a street light at 6 pm? (a) needs AI (learning) (b) a simple rule is enough
  14. 14.🤖 AI or a normal program: which one “follows fixed rules”? (a) AI (b) a normal program
  15. 15.🛠️ Which does this job need: counting the words in an essay? (a) a simple rule is enough (b) needs AI (learning)
  16. 16.Which of these uses AI? (a) a digital watch (b) an image generator (c) a printed timetable (d) a kitchen weighing scale
  17. 17.✅ Is this a real check of an AI answer: it uses big words? (a) a real check (b) not a real check
  18. 18.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
  19. 19.🤖 AI or a normal program: which one “uses rules people wrote”? (a) AI (b) a normal program
  20. 20.Which of these uses AI? (a) a kitchen weighing scale (b) a torch (c) a digital watch (d) face unlock on a phone
  21. 21.🤖 Does an AI system think and feel like a person? (a) only on weekends (b) no, it finds patterns (c) yes, just like us (d) yes, it gets sad
  22. 22.🔍 Which is the odd one out? (a) a doorbell (b) photos grouped by face (c) a printed timetable (d) a stopwatch
  23. 23.Which of these is bad for training a model? (a) very few examples (b) many varied examples (c) clear, sharp examples (d) new data for testing
  24. 24.🔦 Is a torch with an on/off switch AI? (a) only if it is bright (b) yes (c) no
  25. 25.🤔 An AI answer sounds very confident. Does that mean it is right? (a) no, check it anyway (b) yes, if it is long (c) yes, always
  26. 26.Which of these helps reduce bias? (a) fix wrong labels (b) add more of the same (c) skip testing (d) copy old unfair choices
  27. 27.🎨 This prompt asks a generative AI for: five quiz questions on fractions. What kind of output is that? (a) an image (b) text (c) music or sound
  28. 28.🔍 Which is the odd one out? (a) predicting rain (b) unlocking with a face (c) turning speech to text (d) composing a new tune
  29. 29.✨ Generative or not: creating a cartoon? (a) sorts or predicts (b) makes something new
  30. 30.🛠️ Which does this job need: turning spoken words into typed text? (a) a simple rule is enough (b) needs AI (learning)
  31. 31.🏠 AI or not AI: a doorbell? (a) not AI (b) uses AI
  32. 32.🤖 AI or a normal program: which one “never learns from data”? (a) AI (b) a normal program
  33. 33.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your account is locked, pay ₹99 now” (a) not spam (b) spam
  34. 34.Which of these is not AI? (a) a calculator (b) a voice assistant (c) an app translating signs (d) an image generator
  35. 35.🛠️ Which does this job need: ringing the school bell at 9 am? (a) needs AI (learning) (b) a simple rule is enough
  36. 36.⏩ In machine learning, which comes first: tomorrow’s rain guess or past weather records? (a) tomorrow’s rain guess (b) past weather records
  37. 37.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Please buy milk on the way home” (a) not spam (b) spam
  38. 38.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
  39. 39.Which of these is good for training a model? (a) very few examples (b) new data for testing (c) labels added at random (d) only one kind of example
  40. 40.Which of these describes how AI works? (a) uses rules people wrote (b) never learns from data (c) one set rule per case (d) makes a best guess

Answer key

  1. new data for testing
  2. balanced data
  3. examples of every type
  4. a fact
  5. old emails marked spam
  6. AI learns from data
  7. bad for training
  8. AI answers need checking
  9. False
  10. good for training
  11. a prediction
  12. a myth
  13. a simple rule is enough
  14. a normal program
  15. a simple rule is enough
  16. an image generator
  17. not a real check
  18. adds to bias
  19. a normal program
  20. face unlock on a phone
  21. no, it finds patterns
  22. photos grouped by face
  23. very few examples
  24. no
  25. no, check it anyway
  26. fix wrong labels
  27. text
  28. composing a new tune
  29. makes something new
  30. needs AI (learning)
  31. not AI
  32. a normal program
  33. spam
  34. a calculator
  35. a simple rule is enough
  36. past weather records
  37. not spam
  38. balanced data
  39. new data for testing
  40. makes a best guess

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